From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks

Stan Heidema; Ivo V. Stoepker; Gerard Flaherty; Kristina M. Angelo; Richard A.J. Post; Charles Miller; Michael Libman; Davidson H. Hamer; Edwin R. Van Den Heuvel; Ralph Huits

doi:10.1093/jtm/taae013

From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks

Stan Heidema
, Ivo V. Stoepker
, Gerard Flaherty
, Kristina M. Angelo
, Richard A.J. Post
, Charles Miller
, Michael Libman
, Davidson H. Hamer
, Edwin R. Van Den Heuvel
, Ralph Huits

Clinical Medicine and Population Health

Eindhoven University of Technology
International Medical University
US Centers for Disease Control and Prevention
McGill University
Boston University School of Public Health
Boston University School of Medicine
Boston University
Irccs Sacro Cuore Don Calabria Hospital

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

7 Citations (Scopus)

Original language	English
Article number	taae013
Journal	Journal of Travel Medicine
Volume	31
Issue number	4
DOIs	https://doi.org/10.1093/jtm/taae013
Publication status	Published - 1 May 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

artificial intelligence
data science
disease surveillance
outbreak detection
Sentinel event
travel medicine

Access to Document

10.1093/jtm/taae013

Cite this

Heidema, S., Stoepker, I. V., Flaherty, G., Angelo, K. M., Post, R. A. J., Miller, C., Libman, M., Hamer, D. H., Van Den Heuvel, E. R., & Huits, R. (2024). From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks. Journal of Travel Medicine, 31(4), Article taae013. https://doi.org/10.1093/jtm/taae013

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keywords = "artificial intelligence, data science, disease surveillance, outbreak detection, Sentinel event, travel medicine",

author = "Stan Heidema and Stoepker, \{Ivo V.\} and Gerard Flaherty and Angelo, \{Kristina M.\} and Post, \{Richard A.J.\} and Charles Miller and Michael Libman and Hamer, \{Davidson H.\} and \{Van Den Heuvel\}, \{Edwin R.\} and Ralph Huits",

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month = may,

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doi = "10.1093/jtm/taae013",

language = "English",

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}

Heidema, S, Stoepker, IV, Flaherty, G, Angelo, KM, Post, RAJ, Miller, C, Libman, M, Hamer, DH, Van Den Heuvel, ER & Huits, R 2024, 'From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks', Journal of Travel Medicine, vol. 31, no. 4, taae013. https://doi.org/10.1093/jtm/taae013

From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks. / Heidema, Stan; Stoepker, Ivo V.; Flaherty, Gerard et al.
In: Journal of Travel Medicine, Vol. 31, No. 4, taae013, 01.05.2024.

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

TY - JOUR

T1 - From GeoSentinel data to epidemiological insights

T2 - a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks

AU - Heidema, Stan

AU - Stoepker, Ivo V.

AU - Flaherty, Gerard

AU - Angelo, Kristina M.

AU - Post, Richard A.J.

AU - Miller, Charles

AU - Libman, Michael

AU - Hamer, Davidson H.

AU - Van Den Heuvel, Edwin R.

AU - Huits, Ralph

PY - 2024/5/1

Y1 - 2024/5/1

KW - artificial intelligence

KW - data science

KW - disease surveillance

KW - outbreak detection

KW - Sentinel event

KW - travel medicine

UR - https://www.scopus.com/pages/publications/85195113693

U2 - 10.1093/jtm/taae013

DO - 10.1093/jtm/taae013

M3 - Article

C2 - 38236181

AN - SCOPUS:85195113693

SN - 1195-1982

VL - 31

JO - Journal of Travel Medicine

JF - Journal of Travel Medicine

IS - 4

M1 - taae013

ER -

From GeoSentinel data to epidemiological insights: a multidisciplinary effort towards artificial intelligence-supported detection of infectious disease outbreaks

UN SDGs

Keywords

Access to Document

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